Sandri, Erfani and Rustadi, Rustadi (2021) Coal velocity and proximate analysis relationship using Multiple Linear Regression. IOP Publishing.

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Abstract

Coal properties such a velocity (Vp) are essential to building a lateral distribution of coal seam using seismic data. The experimental determination of velocity analysis is sophisticated, long time consumed, and expensive. On the contrary, statistical approaches such as linear regression can be run rapidly. The study's two main objectives were to develop models for coal velocity using well log data variables (density and natural Gamma-Ray) and found the relationship between velocity with proximate analysis results. Multiple linear regression (MLR) methods were applied to estimate Vp's relationship between estimated and proximate analysis. By conducting cross-validation, the prediction analysis of the models has been tested by using R2. The result showed that between Vp estimated versus Vp log have R2 0.80 and Vp estimated versus proximate analysis that reflected have R2 of 0.52. Correlations can estimate the relationship between Vp and proximate analysis, then applied that correlation to distributed in seismic volume to obtain coal seam characteristic

Item Type:	Other
Subjects:	Q Science > QE Geology
Divisions:	Fakultas Teknik (FT) > Prodi Teknik Geofisika
Depositing User:	RUSTADI
Date Deposited:	01 Sep 2022 09:44
Last Modified:	01 Sep 2022 09:44
URI:	http://repository.lppm.unila.ac.id/id/eprint/44606

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